An Adaptive Color Image Segmentation

A novel Adaptive Color Image Segmentation (ACIS) System for color image segmentation is presented. The proposed ACIS system uses a neural network with architecture similar to the multilayer perceptron (MLP) network. The main difference is that neurons here uses a multisigmoid activation function. The multisigmoid function is the key for segmentation. The number of steps i.e. thresholds in the multisigmoid function are dependant on the number of clusters in the image. The threshold values for detecting the clusters and their labels are found automatically from the first order derivative of histograms of saturation and intensity in the HSV color space. Here, the main use of neural network is to detect the number of objects automatically from an image. The advantage of this method is that no a priori knowledge is required to segment the color image. ACIS label the objects with their mean colors. The algorithm is found to be reliable and works satisfactorily on different kinds of color images. Experimental results show that the performance of ACIS is robust on noisy images also

Coarse grained dynamics of the freely cooling granular gas in one dimension

We study the dynamics and structure of clusters in the inhomogeneous clustered regime of a freely cooling granular gas of point particles in one dimension. The coefficient of restitution is modeled as $r_0<1$ or 1 depending on whether the relative speed is greater or smaller than a velocity scale $\delta$. The effective fragmentation rate of a cluster is shown to rise sharply beyond a $\delta$ dependent time scale. This crossover is coincident with the velocity fluctuations within a cluster becoming order $\delta$. Beyond this crossover time, the cluster size distribution develops a nontrivial power law distribution, whose scaling properties are related to those of the velocity fluctuations. We argue that these underlying features are responsible behind the recently observed nontrivial coarsening behaviour in the one dimensional freely cooling granular gas.Comment: 7 Pages, 9 Figure

Probable role of ablation of cerebral ganglia and injection of its extracts on o:n ratio of Lamellidens corrianis during summer season

Amongst invertebrates, molluscs show great variability in their nervous system ranging from primitive arrangement in Chitons to the complex mass of fused ganglia forming the ‘brain’ of cephalopods. Most of the effector organs used for pharmacological or physiological experiments. The neurosecretory cells (NSCs) with their combination of neuronal and glandular capabilities are perfectly suited to translate a neuronal input into the hormonal output best suited to long-term process. In this capacity, the NSCs may produce hormones, which act directly upon the peripheral target or it may exert its effect indirectly by influencing the activity of other non-neural, endocrine organs. Neurosecretory cells have been detected in the cerebral, pedal and visceral ganglia of Lamellidens corrianus. The distribution and biology of freshwater bivalve like Lamellidens corrianus is influenced by local ecological factors (like temperature, pH, inorganic salts, type of soil etc.), water flow system and presence of micro-organisms, teleost fishes and seasonal variations in these parameters. Nitrogenous excretory changes which include ammonia in these molluscs is also influenced by these local ecological factors in which temperature is plays very crucial role. It is well known fact that the high stress conditions during drought or severe winter conditions have been conquered by several lineage of gastropods and sand bivalves and their ability to enter the resistant or dormant stages (low food) protein catabolism increased. Present investigation deals with the oxygen consumption and ammonia excretion ratio of these freshwater pelecypode Lamellidens corrianus. Study on Lemellidens corrianus directed in understanding the different behavioral and physiological aspects after cerebral ganglia removal and injection of their extracts revealed significant changes during summer (April-May)

An Adaptive Color Image Segmentation

A novel Adaptive Color Image Segmentation (ACIS) System for color image segmentation is presented. The proposed ACIS system uses a neural network with architecture similar to the multilayer perceptron (MLP) network. The main difference is that neurons here uses a multisigmoid activation function. The multisigmoid function is the key for segmentation. The number of steps i.e. thresholds in the multisigmoid function are dependant on the number of clusters in the image. The threshold values for detecting the clusters and their labels are found automatically from the first order derivative of histograms of saturation and intensity in the HSV color space. Here, the main use of neural network is to detect the number of objects automatically from an image. The advantage of this method is that no a priori knowledge is required to segment the color image. ACIS label the objects with their mean colors. The algorithm is found to be reliable and works satisfactorily on different kinds of color images. Experimental results show that the performance of ACIS is robust on noisy images also

Site Catchment Analysis of Mahalena Cave of Rajagala, Sri Lanka: With Special Reference to the Prehistoric and Anuradhapura Phase

The systematic archaeological survey was carried out around the 0-10 km radius of Mahalena cave site. Documentation of natural resources available within the estimated radius. A few satellite settlements or supportive settlements were identified within the radius of Mahalena cave. The chief aim of this research is to understand the suitability of the landscape and natural resources available within the vicinity of this archaeological site. Mahalena cave site was subjected to large-scale excavation for several seasons by Sri Lankan and Indian archaeologists. A Few seasons of detailed excavations have provided us with sufficient data to study the resource exploitation pattern around the Mahalena cave. The study of the resource exploitation pattern or site catchment study is one of the important tools to reconstruct the economy of ancient settlers of any particular region. Resources lying within the economic range of individual archaeological sites support ancient inhabitants for their day-to-day living. The current research will be helpful in identifying suitable factors which lead the Prehistoric and Early Historic inhabitants of the Mahalena cave to choose this particular location for their settlement.&nbsp; DOI: http://doi.org/10.31357/fhss/vjhss.v08i02.1

In-situ Magnesium Diboride Superconducting Thin Films grown by Pulsed Laser Deposition

Superconducting thin films of MgB2 were deposited by Pulsed Laser Deposition on magnesium oxide and sapphire substrates. Samples grown at 450C in an argon buffer pressure of about 10-2 mbar by using a magnesium enriched target resulted to be superconducting with a transition temperature of about 25 K. Film deposited from a MgB2 sintered pellet target in ultra high vacuum conditions showed poor metallic or weak semiconducting behavior and they became superconducting only after an ex-situ annealing in Mg vapor atmosphere. Up to now, no difference in the superconducting properties of the films obtained by these two procedures has been evidenced.Comment: 10 pages, 4 figure

Histochemical techniques in plant science: more than meets the eye

Histochemistry is an essential analytical tool interfacing extensively with plant science. The literature is indeed constellated with examples showing its use to decipher specific physiological and developmental processes, as well as to study plant cell structures. Plant cell structures are translucent unless they are stained. Histochemistry allows the identification and localization, at the cellular level, of biomolecules and organelles in different types of cells and tissues, based on the use of specific staining reactions and imaging. Histochemical techniques are also widely used for the in vivo localization of promoters in specific tissues, as well as to identify specific cell wall components such as lignin and polysaccharides. Histochemistry also enables the study of plant reactions to environmental constraints, e.g. the production of reactive oxygen species (ROS) can be traced by applying histochemical staining techniques. The possibility of detecting ROS and localizing them at the cellular level is vital in establishing the mechanisms involved in the sensitivity and tolerance to different stress conditions in plants. This review comprehensively highlights the additional value of histochemistry as a complementary technique to high-throughput approaches for the study of the plant response to environmental constraints. Moreover, here we have provided an extensive survey of the available plant histochemical staining methods used for the localization of metals, minerals, secondary metabolites, cell wall components, and the detection of ROS production in plant cells. The use of recent technological advances like CRISPR/Cas9-based genome-editing for histological application is also addressed. This review also surveys the available literature data on histochemical techniques used to study the response of plants to abiotic stresses and to identify the effects at the tissue and cell levels.The authors would like to thank Head of the Department, University of Allahabad, Allahabad, India, for providing the necessary facilities to carry out the work

Corrigendum to “Counting adolescents in: the development of an adolescent health indicator framework for population-based settings”

The authors were recently made aware of an oversight such that parts of the text in the Introduction and Methods sections, which describe shortcomings in the existing literature and the methods in this work to identify frameworks and indicators, were missing attribution to published work cited elsewhere in the manuscript. To clarify, we adjust the relevant sections to fully attribute the prior work in three areas, as described below. Underlined text is additional to the original: While both school- and community-based modalities can provide nationally representative data among eligible adolescents, several shortcomings in adolescent health measurement in LMICs were noted by the GAMA Advisory Group (Reference 13 as in the original paper). First, these measurements do not equally cover all adolescent subgroups, with evidence gaps being largest for males, younger adolescents aged 10–14 years, adolescents of diverse genders, ethnicities, and religions, as well as those out of school and migrants. Second, age-disaggregated data are often lacking—due in part to incomplete age coverage—limiting their use for program planning. Third, several aspects of adolescent health are inadequately covered including mental health, substance use, injury, sexual and reproductive health among unmarried adolescents, and positive aspects of adolescent health and well-being. Fourth, the definitions and assessment methods used across adolescent health indicator frameworks are inconsistent. For example, adolescent overweight and obesity—a major cause of non-communicable diseases and a public health risk for future and intergeneration health—is inconsistently captured across indicator frameworks and strikingly absent from the SDGs (Reference 13 as in the original paper). Additional shortcomings include, current adolescent health data systems often lack intersectoral coordination beyond health (e.g., with education, water and sanitation, and social protection systems) and suffer from irregularities in coverage and timing (Reference 6 as in the original paper). Broadly, these indicator frameworks and strategy documents captured disease burden, health risks, and prominent social determinants of health during adolescence. To be congruent with the existing global recommendations and guidelines (References 3–7 as in the original paper) and global measurement efforts (References 10 and 16 as in the original paper), the indicator framework documents had to meet three inclusion criteria, as laid out by the GAMA Advisory Group (Reference 14 as in the original paper): (1) provide recommendations about the measurement of adolescents' health and well-being; (2) include indicators for “adolescents” covering the adolescent age range (10–19 years) in the whole or part; and (3) be global or regional in scope. Using the GAMA's approach (Reference 13 as in the original paper), the recommendations of Lancet Adolescent Health Commission (Reference 6 as in the original paper), and several other guidelines (References 7, 9, 12, 17–19 as in the original paper), we selected adolescent health and well-being domains based on four key aspects of adolescents in LMICs: a) population trends; b) disease burden; c) drivers of health inequality; and d) opportunity for interventions